{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Real-world data\n",
    "\n",
    "The section reports the performances that are obtained on real-world data using model selection procedures. The dataset is the same as in [Chapter 3, Section 5](Baseline_FDS_RealWorldData). We first report the training performance versus test performance for decision trees. We then compare the gains of performances that can be obtained with prequential validation, for decision trees, logistic regression, random forests and boosting trees.  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "# Initialization: Load shared functions and simulated data \n",
    "\n",
    "# Load shared functions\n",
    "!curl -O https://raw.githubusercontent.com/Fraud-Detection-Handbook/fraud-detection-handbook/main/Chapter_References/shared_functions.py\n",
    "%run shared_functions.py\n",
    "#%run ../Chapter_References/shared_functions.ipynb\n",
    "\n",
    "# Get simulated data from Github repository\n",
    "if not os.path.exists(\"simulated-data-transformed\"):\n",
    "    !git clone https://github.com/Fraud-Detection-Handbook/simulated-data-transformed\n",
    "        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training performance versus test performance\n",
    "\n",
    "In [Section 2.1 of this chapter](Training_Vs_Test_Performances), we illustrated the overfitting phenomenon with decision trees by comparing the training and test performances when the maximum tree depth is increased. We ran the same experiments on real-world data, and saved the resulting performance DataFrame as a Pickle file in  `performances_train_test_real_world_data.pkl`. Let us first load the file. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "filehandler = open('images/performances_train_test_real_world_data.pkl', 'rb') \n",
    "performances_df = pickle.load(filehandler)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The DataFrame contains the same information as in [Section 2.1](Training_Vs_Test_Performances), for the real-world transaction data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC ROC Test</th>\n",
       "      <th>Average precision Test</th>\n",
       "      <th>Card Precision@100 Test</th>\n",
       "      <th>AUC ROC Train</th>\n",
       "      <th>Average precision Train</th>\n",
       "      <th>Card Precision@100 Train</th>\n",
       "      <th>Execution time</th>\n",
       "      <th>Parameters summary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.626</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.077</td>\n",
       "      <td>0.639</td>\n",
       "      <td>0.063</td>\n",
       "      <td>0.147</td>\n",
       "      <td>19.533309</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.715</td>\n",
       "      <td>0.032</td>\n",
       "      <td>0.134</td>\n",
       "      <td>0.736</td>\n",
       "      <td>0.094</td>\n",
       "      <td>0.233</td>\n",
       "      <td>22.060830</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.755</td>\n",
       "      <td>0.037</td>\n",
       "      <td>0.149</td>\n",
       "      <td>0.792</td>\n",
       "      <td>0.121</td>\n",
       "      <td>0.251</td>\n",
       "      <td>24.506536</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.791</td>\n",
       "      <td>0.045</td>\n",
       "      <td>0.187</td>\n",
       "      <td>0.815</td>\n",
       "      <td>0.154</td>\n",
       "      <td>0.317</td>\n",
       "      <td>27.029386</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.812</td>\n",
       "      <td>0.049</td>\n",
       "      <td>0.196</td>\n",
       "      <td>0.847</td>\n",
       "      <td>0.184</td>\n",
       "      <td>0.351</td>\n",
       "      <td>29.506857</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.826</td>\n",
       "      <td>0.029</td>\n",
       "      <td>0.114</td>\n",
       "      <td>0.868</td>\n",
       "      <td>0.213</td>\n",
       "      <td>0.414</td>\n",
       "      <td>32.073183</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.838</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.070</td>\n",
       "      <td>0.886</td>\n",
       "      <td>0.244</td>\n",
       "      <td>0.467</td>\n",
       "      <td>34.493712</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.831</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.049</td>\n",
       "      <td>0.895</td>\n",
       "      <td>0.282</td>\n",
       "      <td>0.500</td>\n",
       "      <td>37.152258</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.831</td>\n",
       "      <td>0.018</td>\n",
       "      <td>0.056</td>\n",
       "      <td>0.907</td>\n",
       "      <td>0.322</td>\n",
       "      <td>0.566</td>\n",
       "      <td>39.713055</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.520</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.014</td>\n",
       "      <td>0.973</td>\n",
       "      <td>0.758</td>\n",
       "      <td>0.983</td>\n",
       "      <td>63.055570</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.545</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.017</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>76.632960</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    AUC ROC Test  Average precision Test  Card Precision@100 Test  \\\n",
       "0          0.626                   0.024                    0.077   \n",
       "1          0.715                   0.032                    0.134   \n",
       "2          0.755                   0.037                    0.149   \n",
       "3          0.791                   0.045                    0.187   \n",
       "4          0.812                   0.049                    0.196   \n",
       "5          0.826                   0.029                    0.114   \n",
       "6          0.838                   0.020                    0.070   \n",
       "7          0.831                   0.020                    0.049   \n",
       "8          0.831                   0.018                    0.056   \n",
       "9          0.520                   0.008                    0.014   \n",
       "10         0.545                   0.003                    0.017   \n",
       "\n",
       "    AUC ROC Train  Average precision Train  Card Precision@100 Train  \\\n",
       "0           0.639                    0.063                     0.147   \n",
       "1           0.736                    0.094                     0.233   \n",
       "2           0.792                    0.121                     0.251   \n",
       "3           0.815                    0.154                     0.317   \n",
       "4           0.847                    0.184                     0.351   \n",
       "5           0.868                    0.213                     0.414   \n",
       "6           0.886                    0.244                     0.467   \n",
       "7           0.895                    0.282                     0.500   \n",
       "8           0.907                    0.322                     0.566   \n",
       "9           0.973                    0.758                     0.983   \n",
       "10          1.000                    1.000                     1.000   \n",
       "\n",
       "    Execution time  Parameters summary  \n",
       "0        19.533309                   2  \n",
       "1        22.060830                   3  \n",
       "2        24.506536                   4  \n",
       "3        27.029386                   5  \n",
       "4        29.506857                   6  \n",
       "5        32.073183                   7  \n",
       "6        34.493712                   8  \n",
       "7        37.152258                   9  \n",
       "8        39.713055                  10  \n",
       "9        63.055570                  20  \n",
       "10       76.632960                  50  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performances_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us plot the performances in terms of AUC ROC, Average Precision, and CP@100, using the `get_performances_plots` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "get_performances_plots(performances_df, \n",
    "                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'], \n",
    "                       expe_type_list=['Test','Train'],expe_type_color_list=['#008000','#2F4D7E'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We observe that the results are qualitatively very similar to [those obtained on simulated data](Training_Vs_Test_Performances). The overfitting phenomenon is clearly present: As the tree depth increases, so does the performance for all metrics (blue lines), reaching optimal performances for a tree depth of 50. The test performance however peaks for a tree depth between 5 and 10, and then decreases for higher values of the parameter.\n",
    "\n",
    "Thanks to the reproducibility of experiments, we note that the performances obtained for a tree depth of 2 and 50 match those reported in [Chapter 3](Chapter3_BaselineWL). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model performances per model class\n",
    "\n",
    "Let us explore more extensively how model selection improves performances using prequential validation on real-world data. We report in the following the results for the four classes of models, following the same experimental setup than in the [previous section](Model_Selection). The results are available in the `performances_model_selection_real_world_data.pkl` Pickle file. Let us first load the file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "filehandler = open('images/performances_model_selection_real_world_data.pkl', 'rb') \n",
    "(performances_df_dictionary, execution_times) = pickle.load(filehandler)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The results are in the same format as in the [previous section](Model_Selection). The performances are summarized as a dictionary in the `performances_df_dictionary`, where keys correspond to models.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['Decision Tree', 'Random Forest', 'XGBoost', 'Logistic Regression'])"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performances_df_dictionary.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The execution times for each models are stored in the `execution_times` list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1617.0470759868622,\n",
       " 694.7196891307831,\n",
       " 3615.5994658470154,\n",
       " 8788.51293516159,\n",
       " 5527.099639177322]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "execution_times"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Model_Selection_RWD_Decision_Trees)=\n",
    "### Decision trees\n",
    " \n",
    "The validation and test performances as a function of tree depth are reported below, together with the summary of optimal parameters and performances."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "performances_df_dt=performances_df_dictionary['Decision Tree']\n",
    "summary_performances_dt=get_summary_performances(performances_df_dt, parameter_column_name=\"Parameters summary\")\n",
    "\n",
    "get_performances_plots(performances_df_dt, \n",
    "                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'], \n",
    "                       expe_type_list=['Test','Validation'], expe_type_color_list=['#008000','#FF0000'],\n",
    "                       summary_performances=summary_performances_dt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC ROC</th>\n",
       "      <th>Average precision</th>\n",
       "      <th>Card Precision@100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Best estimated parameters</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Validation performance</th>\n",
       "      <td>0.861+/-0.01</td>\n",
       "      <td>0.065+/-0.02</td>\n",
       "      <td>0.214+/-0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Test performance</th>\n",
       "      <td>0.869+/-0.03</td>\n",
       "      <td>0.068+/-0.01</td>\n",
       "      <td>0.232+/-0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal parameter(s)</th>\n",
       "      <td>8</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal test performance</th>\n",
       "      <td>0.872+/-0.02</td>\n",
       "      <td>0.068+/-0.01</td>\n",
       "      <td>0.232+/-0.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                AUC ROC Average precision Card Precision@100\n",
       "Best estimated parameters             7                 6                  6\n",
       "Validation performance     0.861+/-0.01      0.065+/-0.02       0.214+/-0.04\n",
       "Test performance           0.869+/-0.03      0.068+/-0.01       0.232+/-0.04\n",
       "Optimal parameter(s)                  8                 6                  6\n",
       "Optimal test performance   0.872+/-0.02      0.068+/-0.01       0.232+/-0.04"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_performances_dt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar to the simulated dataset results, the validation peformances provide good estimates of the test performances. The optimal tree depth, between 6 and 9 depending on the performance metric, is higher than with the simulated data. This can be explained by the more complex relationships between input features and fraud label in the real-world dataset. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Model_Selection_RWD_Logistic_Regression)=\n",
    "### Logistic regression\n",
    " \n",
    "The validation and test performances as a function of the regulization value are reported below, together with the summary of optimal parameters and performances."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "performances_df_lr=performances_df_dictionary['Logistic Regression']\n",
    "summary_performances_lr=get_summary_performances(performances_df_lr, parameter_column_name=\"Parameters summary\")\n",
    "\n",
    "get_performances_plots(performances_df_lr, \n",
    "                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'], \n",
    "                       expe_type_list=['Test','Validation'], expe_type_color_list=['#008000','#FF0000'],\n",
    "                       parameter_name='Regularization value',\n",
    "                       summary_performances=summary_performances_lr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC ROC</th>\n",
       "      <th>Average precision</th>\n",
       "      <th>Card Precision@100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Best estimated parameters</th>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Validation performance</th>\n",
       "      <td>0.786+/-0.02</td>\n",
       "      <td>0.041+/-0.02</td>\n",
       "      <td>0.171+/-0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Test performance</th>\n",
       "      <td>0.816+/-0.02</td>\n",
       "      <td>0.054+/-0.01</td>\n",
       "      <td>0.211+/-0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal parameter(s)</th>\n",
       "      <td>0.1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal test performance</th>\n",
       "      <td>0.816+/-0.02</td>\n",
       "      <td>0.054+/-0.01</td>\n",
       "      <td>0.212+/-0.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                AUC ROC Average precision Card Precision@100\n",
       "Best estimated parameters           0.1               0.1                0.1\n",
       "Validation performance     0.786+/-0.02      0.041+/-0.02       0.171+/-0.03\n",
       "Test performance           0.816+/-0.02      0.054+/-0.01       0.211+/-0.03\n",
       "Optimal parameter(s)                0.1               1.0               10.0\n",
       "Optimal test performance   0.816+/-0.02      0.054+/-0.01       0.212+/-0.04"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary_performances_lr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar to [the simulated dataset](Model_Selection_Logistic_Regression), the regulization value has little influence on the performances. The performances are stable across the range of tested regularization values."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Model_Selection_RWD_RF)=\n",
    "### Random forest\n",
    "\n",
    "Two different parameters are assessed for random forests: The tree depth (`max_depth` parameter), taking values in the set [5,10,20,50], and the number of trees (`n_estimators` parameter), taking values in the set [25,50,100]. Overall, the optimal parameters are a combination of 100 trees with a maximum depth of 10.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC ROC</th>\n",
       "      <th>Average precision</th>\n",
       "      <th>Card Precision@100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Best estimated parameters</th>\n",
       "      <td>25/10</td>\n",
       "      <td>100/10</td>\n",
       "      <td>100/10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Validation performance</th>\n",
       "      <td>0.917+/-0.0</td>\n",
       "      <td>0.093+/-0.02</td>\n",
       "      <td>0.258+/-0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Test performance</th>\n",
       "      <td>0.912+/-0.02</td>\n",
       "      <td>0.08+/-0.03</td>\n",
       "      <td>0.227+/-0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal parameter(s)</th>\n",
       "      <td>100/10</td>\n",
       "      <td>100/10</td>\n",
       "      <td>50/5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal test performance</th>\n",
       "      <td>0.912+/-0.02</td>\n",
       "      <td>0.08+/-0.03</td>\n",
       "      <td>0.227+/-0.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                AUC ROC Average precision Card Precision@100\n",
       "Best estimated parameters         25/10            100/10             100/10\n",
       "Validation performance      0.917+/-0.0      0.093+/-0.02       0.258+/-0.03\n",
       "Test performance           0.912+/-0.02       0.08+/-0.03       0.227+/-0.05\n",
       "Optimal parameter(s)             100/10            100/10               50/5\n",
       "Optimal test performance   0.912+/-0.02       0.08+/-0.03       0.227+/-0.04"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performances_df_rf=performances_df_dictionary['Random Forest']\n",
    "summary_performances_rf=get_summary_performances(performances_df_rf, parameter_column_name=\"Parameters summary\")\n",
    "summary_performances_rf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For better visualization, we follow the same approach as with the [simulated dataset](Model_Selection_Random_Forest). Let us first report the performances as a function of the tree depth, for a fixed number of 100 trees.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "performances_df_rf_fixed_number_of_trees=performances_df_rf[performances_df_rf[\"Parameters summary\"].str.startswith(\"100\")]\n",
    "\n",
    "summary_performances_fixed_number_of_trees=get_summary_performances(performances_df_rf_fixed_number_of_trees, parameter_column_name=\"Parameters summary\")\n",
    "\n",
    "get_performances_plots(performances_df_rf_fixed_number_of_trees, \n",
    "                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'], \n",
    "                       expe_type_list=['Test','Validation'], expe_type_color_list=['#008000','#FF0000'],\n",
    "                       parameter_name=\"Number of trees/Maximum tree depth\",\n",
    "                       summary_performances=summary_performances_fixed_number_of_trees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar to the [simulated dataset](Model_Selection_Random_Forest), the peformances first increase with the tree depth, before reaching an optimum and decreasing. The optimal tree depth is found around 10.\n",
    "\n",
    "Let us then report the performances as a function of the number of trees, for a fixed depth of 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "performances_df_rf_fixed_max_tree_depth=performances_df_rf[performances_df_rf[\"Parameters summary\"].str.endswith(\"10\")]\n",
    "\n",
    "summary_performances_fixed_max_tree_depth=get_summary_performances(performances_df_rf_fixed_max_tree_depth, parameter_column_name=\"Parameters summary\")\n",
    "\n",
    "get_performances_plots(performances_df_rf_fixed_max_tree_depth, \n",
    "                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'], \n",
    "                       expe_type_list=['Test','Validation'], expe_type_color_list=['#008000','#FF0000'],\n",
    "                       parameter_name=\"Number of trees/Maximum tree depth\",\n",
    "                       summary_performances=summary_performances_fixed_max_tree_depth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Increasing the number of trees allows to slighlty increase the Average Precicision and the CP@100. It however has little influence on the AUC ROC, for which 25 trees already provide optimal performances.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Model_Selection_RWD_XGBoost)=\n",
    "### XGBoost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Three different parameters are assessed for boosting: The tree depth (`max_depth` parameter) taking values in the set [3,6,9], the number of trees (`n_estimators` parameter) taking values in the set [25,50,100] and the learning rate (`learning_rate` parameter) taking values in the set [0.1, 0.3]. The optimal parameters are a combination of 100 trees with a maximum depth of 6, and a learning rate of 0.1, except for the CP@100 where 50 trees provide the best performance. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AUC ROC</th>\n",
       "      <th>Average precision</th>\n",
       "      <th>Card Precision@100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Best estimated parameters</th>\n",
       "      <td>100/0.1/6</td>\n",
       "      <td>100/0.1/6</td>\n",
       "      <td>100/0.1/6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Validation performance</th>\n",
       "      <td>0.924+/-0.01</td>\n",
       "      <td>0.102+/-0.02</td>\n",
       "      <td>0.261+/-0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Test performance</th>\n",
       "      <td>0.928+/-0.01</td>\n",
       "      <td>0.095+/-0.03</td>\n",
       "      <td>0.235+/-0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal parameter(s)</th>\n",
       "      <td>100/0.1/6</td>\n",
       "      <td>100/0.1/6</td>\n",
       "      <td>50/0.1/6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Optimal test performance</th>\n",
       "      <td>0.928+/-0.01</td>\n",
       "      <td>0.095+/-0.03</td>\n",
       "      <td>0.249+/-0.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                AUC ROC Average precision Card Precision@100\n",
       "Best estimated parameters     100/0.1/6         100/0.1/6          100/0.1/6\n",
       "Validation performance     0.924+/-0.01      0.102+/-0.02       0.261+/-0.02\n",
       "Test performance           0.928+/-0.01      0.095+/-0.03       0.235+/-0.07\n",
       "Optimal parameter(s)          100/0.1/6         100/0.1/6           50/0.1/6\n",
       "Optimal test performance   0.928+/-0.01      0.095+/-0.03       0.249+/-0.04"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performances_df_xgboost=performances_df_dictionary['XGBoost']\n",
    "summary_performances_xgboost=get_summary_performances(performances_df_xgboost, parameter_column_name=\"Parameters summary\")\n",
    "summary_performances_xgboost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For better visualization, we follow the same approach as with the [simulated dataset](Model_Selection_XGBoost). Let us first report the performances as a function of the tree depth, for a fixed number of 100 trees and a learning rate of 0.1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "performances_df_xgboost_fixed_number_of_trees=performances_df_xgboost[performances_df_xgboost[\"Parameters summary\"].str.startswith(\"100/0.1\")]\n",
    "\n",
    "summary_performances_fixed_number_of_trees=get_summary_performances(performances_df_xgboost_fixed_number_of_trees, parameter_column_name=\"Parameters summary\")\n",
    "\n",
    "get_performances_plots(performances_df_xgboost_fixed_number_of_trees, \n",
    "                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'], \n",
    "                       expe_type_list=['Test','Validation'], expe_type_color_list=['#008000','#FF0000'],\n",
    "                       parameter_name=\"Number of trees/Maximum tree depth\",\n",
    "                       summary_performances=summary_performances_fixed_number_of_trees)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar to the [simulated dataset](Model_Selection_XGBoost), the peformances first increase with the tree depth, before reaching an optimum and decreasing. The optimal tree depth is found around 6.\n",
    "\n",
    "Let us then report the performances as a function of the number of trees, for a fixed depth of 6 and a learning rate 0.1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "performances_df_xgboost_fixed_max_tree_depth=performances_df_xgboost[performances_df_xgboost[\"Parameters summary\"].str.endswith(\"0.1/6\")]\n",
    "\n",
    "summary_performances_fixed_max_tree_depth=get_summary_performances(performances_df_xgboost_fixed_max_tree_depth, parameter_column_name=\"Parameters summary\")\n",
    "\n",
    "get_performances_plots(performances_df_xgboost_fixed_max_tree_depth, \n",
    "                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'], \n",
    "                       expe_type_list=['Test','Validation'], expe_type_color_list=['#008000','#FF0000'],\n",
    "                       parameter_name=\"Number of trees/Maximum tree depth\",\n",
    "                       summary_performances=summary_performances_fixed_max_tree_depth)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Increasing the number of trees allows to increase the AUC ROC and the Average Precicision. We however note that for the CP@100, a decrease of performance occurs after 50 trees for the test set.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Model_Selection_RWD_Comparison)=\n",
    "## Comparison of model performances: Summary\n",
    "\n",
    "Let us finally compare the performances of the different classes of models. Similar to [the simulated dataset](Model_Selection_Comparison_Performances), we plot the performances for the four model classes and for each performance metric as bar charts using the `get_model_selection_performances_plots` function.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "get_model_selection_performances_plots(performances_df_dictionary, \n",
    "                                       performance_metrics_list=['AUC ROC', 'Average precision', 'Card Precision@100'],\n",
    "                                       ylim_list=[[0.5,1],[0,0.2],[0,0.35]],\n",
    "                                       model_classes=['Decision Tree', \n",
    "                                                      'Logistic Regression', \n",
    "                                                      'Random Forest', \n",
    "                                                      'XGBoost'])\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As for the simulated data, XGBoost is the model class that provides the best performances for the three metrics (Optimal parameters, represented with blue bars). It is however worth noting that for CP@100, the XGboost optimal parameters are actually not found by the model selection procedure, resulting in lower performances. The actual performances in terms of CP@100 are slightly better than random forests, and on par with decision trees.\n",
    "\n",
    "This is a result worth considering: Thanks to model selection, the decision tree model is actually as performant than XGBoost, and more performant than random forests in terms of CP@100. The execution times for decision trees are however much lower than those of random forests and XGBoost, as is reported below.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "%%capture\n",
    "\n",
    "fig_model_selection_execution_times_for_each_model_class, ax = plt.subplots(1, 1, figsize=(5,4))\n",
    "\n",
    "model_classes=['Decision Tree','Logistic Regression','Random Forest','XGBoost']\n",
    "    \n",
    "# width of the bars\n",
    "barWidth = 0.3\n",
    "# The x position of bars\n",
    "r1 = np.arange(len(model_classes))\n",
    "    \n",
    "# Create execution times bars\n",
    "ax.bar(r1, execution_times[0:4], \n",
    "        width = barWidth, color = 'black', edgecolor = 'black', \n",
    "        capsize=7)\n",
    "\n",
    "ax.set_xticks(r1+barWidth/2)\n",
    "ax.set_xticklabels(model_classes, rotation = 45, ha=\"right\", fontsize=12)\n",
    "ax.set_title('Model selection execution times \\n for different model classes', fontsize=18)\n",
    "ax.set_xlabel(\"Model class\", fontsize=16)\n",
    "ax.set_ylabel(\"Execution times (s)\", fontsize=15)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x288 with 1 Axes>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig_model_selection_execution_times_for_each_model_class"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It should be kept in mind that experiments were run on a 40 core server, with parallel computing enabled for random forests and XGBoost. Therefore, the model selection procedure for decision trees is in fact one to two order of magnitude faster than for random forests and XGBoost.\n",
    "\n",
    "As a final remark, we note that logistic regression models were the fastest to train, but also provided the worst performances for all metrics. "
   ]
  }
 ],
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   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
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 },
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